import cv2
import os
import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
%matplotlib inline

# Get current working directory
cwd = os.getcwd()
print(cwd)

# Read the csv file into a data frame
driving_log_df = pd.read_csv('driving_log.csv')
print(driving_log_df.shape)

X_data_set = np.empty([len(driving_log_df['Center'])*3, 32, 32, 3])
Y_data_set = np.empty(len(driving_log_df['Center'])*3)
print(X_data_set.shape)
print(Y_data_set.shape)

# Path to images
images_path = cwd + "/IMG"
print(images_path)

# Index
index = 0

for file in os.listdir(images_path):
    image = cv2.imread(os.path.join(images_path, file), cv2.IMREAD_COLOR)
    image = cv2.resize(image, (32, 32))

    # OpenCV reads images in the BGR format, convert them into RGB
    image_rgb =  cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    # Copy the image
    X_data_set[index] = np.copy(image_rgb)

    # Display images
    if(index==0):
        figure1 = plt.figure()
        plt.imshow(image_rgb)
        figure2 = plt.figure()
        plt.imshow(X_data_set[0])

    index = index + 1